| --- |
| license: other |
| task_categories: |
| - visual-question-answering |
| language: |
| - en |
| --- |
| |
| # chrome_writting_cleaned |
|
|
| The **chrome_writting__x** family of the ElliotVL supervised-fine-tuning pool, **after VLM cleaning**. |
| |
| | | | |
| |---|---| |
| | images | 16,542 | |
| | QA turns | 41,399 | |
| | answers rewritten by the cleaning pass | 1,748 | |
| | QA created by the cleaning pass (`new_qa`) | 26,791 (64.7%) | |
| | shards | 1 | |
| |
| ## How this was cleaned |
| |
| A vision-language model read each image together with its QA and judged the item. The pass is |
| **not a filter that only removes rows** — it rewrites answers it finds wrong but salvageable, |
| drops what it cannot salvage, and adds QA where the image supports more than the source provided. |
| Each row carries the judge's own record in `clean_meta`, including the cleaner identity, the |
| policy it applied, and its per-item scores for legibility, richness and coverage. |
|
|
| **A large share of the QA here was written by the cleaning pass, not by the original dataset.** |
| Across the pool that share runs from roughly half to over 80% of a family's turns, and it is |
| reported in the table above. Those rows have an empty `org_answer` because no pre-clean original |
| exists. Treat them as model-generated supervision: they were judged against the image, but they |
| are not human annotation, and model-written QA is where formatting defects are most likely. |
|
|
| The effect on the answers that *were* carried over is substantive rather than cosmetic. In this pool the pass corrects values, not just |
| wording — a curve's critical point restated from `4.00` to `2.00`, a computed ratio from `1` to |
| `Approximately 1.33` — and for some families it removed the content entirely, which is why those |
| families are absent here rather than published empty. |
|
|
| ## `answer` vs `org_answer` |
| |
| - `answer` — the cleaned answer. **Train on this.** |
| - `org_answer` — the pre-cleaning answer from the same `(image, question)` in the uncleaned pool. |
| It is empty for QA the cleaning pass added, which have no original. |
|
|
| Where the two differ, the difference is the correction. Keeping both makes every edit auditable |
| instead of asking you to take the cleaning on trust. |
|
|
|
|
|
|
| ## Schema |
|
|
| - `image` — HF `Image()`, renders directly in the dataset viewer |
| - `image_sha256` — content hash of the image |
| - `n_qa` — number of turns attached to this image |
| - `qa` — list of {`question`, `answer`, `org_answer`}, **in source order** |
| - `family` / `clean_meta` — provenance and the judge's per-row record |
|
|
| A row with more than one entry in `qa` is a **conversation over a single image**, not a set of |
| independent questions — the turns depend on each other and the image belongs to all of them. |
| Keep them together and in order when training. |
|
|
| Parquet row groups are written at ~32 MB so the dataset viewer pages without stalling. |
|
|
| ## What is NOT claimed |
|
|
| No rejection sampling was run against this family: there is no accept/reject verdict per row, and |
| `answer` is the cleaned reference rather than a model generation that a string verifier confirmed. |
| For that, use the `*_RS_think` / `*_rejected` datasets in [elliot-mllm](https://huggingface.co/elliot-mllm). |
|
|
|
|
| ## Examples |
| 10 rows taken straight from this dataset. Images are the **original files** as stored here - no downscaling, no recompression - and every turn is shown in full. |
|
|
| ### Example 1 |
|
|
|  |
|
|
| | # | question | answer | |
| |---|---|---| |
| | 1 | Describe the visual style of the text and the background color. | White handwritten text on a black background. | |
|
|
|
|
| ### Example 2 — 3 turns on one image |
|
|
|  |
|
|
| | # | question | answer | |
| |---|---|---| |
| | 1 | <image><br>Please write out the expression of the formula in the image using LaTeX format. | \frac { - b + \sqrt { b ^ { 2 } - 4 a c } } { 2 a } | |
| | 2 | What is the background color of the image? | Black | |
| | 3 | Is the formula in the image typed or handwritten? | Handwritten | |
|
|
|
|
| ### Example 3 — 4 turns on one image |
|
|
|  |
|
|
| | # | question | answer | |
| |---|---|---| |
| | 1 | <image><br>Please write out the expression of the formula in the image using LaTeX format. | \sum _ { m = 0 } ^ { M } \sum _ { n = 0 } ^ { N } a _ { m , n } | |
| | 2 | What is the background color of the image? | Black | |
| | 3 | What is the writing style of the formula? | Handwritten | |
| | 4 | What color is the text in the image? | White | |
|
|
|
|
| ### Example 4 — 2 turns on one image |
|
|
|  |
|
|
| | # | question | answer | |
| |---|---|---| |
| | 1 | <image><br>Please write out the expression of the formula in the image using LaTeX format. | f = d ^ { 5 } a _ { 4 } + 5 b d ^ { 4 } a _ { 5 } = - 3 2 | |
| | 2 | What are the visual characteristics of the text in the image? | The text appears to be handwritten in white ink on a black background. | |
|
|
|
|
| ### Example 5 — 2 turns on one image |
|
|
|  |
|
|
| | # | question | answer | |
| |---|---|---| |
| | 1 | <image><br>Please write out the expression of the formula in the image using LaTeX format. | \lim _ { x \rightarrow \infty } \int _ { 0 } ^ { x } e ^ { - y ^ { 2 } } d y = \frac { \sqrt { \pi } } { 2 } | |
| | 2 | Describe the visual style and color scheme of the equation in the image. | The equation is handwritten in white script against a solid black background. | |
|
|
|
|
| ### Example 6 — 2 turns on one image |
|
|
|  |
|
|
| | # | question | answer | |
| |---|---|---| |
| | 1 | <image><br>Please write out the expression of the formula in the image using LaTeX format. | N | |
| | 2 | What are the colors of the character and the background in the image? | The character is white and the background is black. | |
|
|
|
|
| ### Example 7 — 3 turns on one image |
|
|
|  |
|
|
| | # | question | answer (cleaned) | org_answer (pre-judge) | |
| |---|---|---|---| |
| | 1 | <image><br>Please write out the expression of the formula in the image using LaTeX format. | T^{C+L}(m) | T ^ { c + L } ( m ) | |
| | 2 | What are the colors of the text and the background in the image? | The text is white and the background is black. | _(unchanged)_ | |
| | 3 | How is the term 'C+L' positioned relative to the letter 'T'? | It is written as a superscript above and to the right of the letter T. | _(unchanged)_ | |
|
|
|
|
| ### Example 8 — 4 turns on one image |
|
|
|  |
|
|
| | # | question | answer | |
| |---|---|---| |
| | 1 | <image><br>Please write out the expression of the formula in the image using LaTeX format. | m ^ { b } | |
| | 2 | What is the background color of the image? | Black | |
| | 3 | What is the color of the mathematical expression? | White | |
| | 4 | How is the letter 'b' positioned relative to the letter 'm'? | It is positioned as a superscript to the upper right. | |
|
|
|
|
| ### Example 9 — 2 turns on one image |
|
|
|  |
|
|
| | # | question | answer | |
| |---|---|---| |
| | 1 | <image><br>Please write out the expression of the formula in the image using LaTeX format. | \log _ { 2 } \frac { 1 } { 2 } + \log _ { 4 } \frac { 2 } { 4 } | |
| | 2 | Describe the visual style and color scheme of the text in the image. | The text is handwritten in white on a black background. | |
|
|
|
|
| ### Example 10 — 2 turns on one image |
|
|
|  |
|
|
| | # | question | answer | |
| |---|---|---| |
| | 1 | <image><br>Please write out the expression of the formula in the image using LaTeX format. | \sum _ { m } f ( m + 3 ) | |
| | 2 | What are the colors of the text and the background in the image? | The text is white and the background is black. | |
|
|
|
|
